论文标题
关键随机图中组件大小的简单路径
A simple path to component sizes in critical random graphs
论文作者
论文摘要
我们根据纳克米亚和佩雷斯的martingale参数以及随机步行估计的曲折论点描述了一种强大的方法，以在几个随机图中获得最大成分的大小的简单上限和下限，\ textit \ textit {crigitality}。即使主要结果并不是什么新鲜事物，我们认为这里提出的材料很有趣，因为它将文献中发现的几个证据统一为一个共同的框架。更具体地说，我们提供易于检查的条件，在满足时，允许立即推导上述界限。
We describe a robust methodology, based on the martingale argument of Nachmias and Peres and random walk estimates, to obtain simple upper and lower bounds on the size of a maximal component in several random graphs \textit{at criticality}. Even though the main result is not new, we believe the the material presented here is interesting because it unifies several proofs found in the literature into a common framework. More specifically, we give easy-to-check conditions that, when satisfied, allow an immediate derivation of the above mentioned bounds.
